1. Field of the Invention
The invention relates to semiconductor processing and the prediction of structures and properties resulting from processes used in the preparation and modification of semiconductor materials. The prediction can be embodied in methods which can be implemented in hardware or software.
2. Description of the Related Art
In order to maximize the performance and value of electronic devices including memories, central processor units (CPUs), transmitters and detectors of electromagnetic and sonic radiation, and other components of electronic computers, it is important to reduce the size, noise, and reproducibility while increasing the speed of the devices. This requires growing complex heterostructures in which various dopants are introduced into precise locations and processed to obtain desired distributions, electrical activity, and other properties useful in devices. To optimize the performance of these devices, it is necessary to model and simulate the electrical and mechanical properties resulting from various distributions and clustering of the dopants, oxidation-products, and impurities. With previous technologies, modeling and simulation techniques have generally treated the materials as a macroscopic continuum, with continuous variations in concentrations of dopants, and have used finite element analysis to describe the diffusion and operation of the devices.
In future generations of devices, the size of device elements (for example the gate of a field effect transistor (FET)) will be in the range of less than 100 nm, a size range at which it will be important to consider the atomistic characteristics of the materials, rather than just their macroscopic continuum properties. For example, to make a p-type silicon FET with a gate less than 100 nm, it is useful to carry out ultra-shallow ion implantation deposition of boron, using low energies (e.g., 1 keV) that limit the boron to a region within a short distance (e.g., 20 nm) from the surface. It is useful to deposit sufficiently high boron surface concentrations (e.g., 5×1020) near the surface to obtain sufficient activity of dopants for optimum performance. However, it is found that such conditions may lead to a clustering of the dopants and other defects (vacancies and interstitials) and to long-range diffusion tails that degrade the performance, whereas it is desired to maintain the boron near the surface while unclustered in a substitutional site that maximizes performance. In addition, it is possible that too much of the boron near the surface may diffuse to the interface, resulting in a kink or non-optimum distribution in the boron distribution. Also, much of the boron may not have the proper electrical activity (as a low energy acceptor level) due to clustering or association with a non-optimum site. These examples consider boron because there are serious problems today involving such systems; however, similar problems can occur for other dopants.
In order to develop the highest performance devices, it is important to accurately predict such properties, that is, to predict the distributions of the dopants and defects (e.g., vacancies, interstitials) as a function of depositing conditions and subsequent heat treatments (e.g., annealing), oxidation, exposure to other impurities or dopants, changes in external conditions (pressure, stress, voltage, magnetic fields, electromagnetic radiation, ultrasonic radiation, etc.). In addition, it is important to predict the electrical activity and other device properties resulting from the deposition and processing of such systems. Also, it is important to predict the critical voltages and fields for electrical or mechanical breakdown of such systems. It is also important to predict the effects of aging (repeated cycling of voltages, stresses, temperature, and exposure to radiation, oxygen, water, and other molecules).